Features of the Development of the Digital Educational Environment in Russia
Bibliographic record
Abstract
Goal of the investigation: This article aims to distinguish the characteristics of the development of the digital educational environment in Russia in the context of the global digitalization process, and to identify threats to information security. Methodology: The leading method for studying this problem is a comparative analysis of the level of evolution of the digital administration in various nations of the world, which passes to comprehensively estimate the obstacle of receiving the learning and informative space as a portion in the sustainable expansion of the Russian economy. Results: The authors revealed the peculiarities of the Russian “digitalization” management system, which is still distinguished by spontaneity and the lack of a coordinated action program on the part of the state. It was revealed that Russia has the necessary potential for the further development of the digital economy: the scientific and intellectual base, a good level of secondary and higher technical education. The article substantiates the results of the development of the Russian digital educational environment: a data source (portal) has been created that is convenient to all levels of residents and stores each user with entrance to online classes for all levels of training and online support for mastering general education subjects; an infrastructure has been created to train teachers and administrative staff, to spread the experience of introducing successful methods and practices of online learning, to track the dynamics of creating a digital educational environment; and a system of advanced training for teachers in the development, use and examination of online courses has been created. Applications of this study: The materials of the article can be useful to relevant state and economic institutions for the formation of a mechanism for informatization of the country's development management system and education in particular, which is part of certain development strategies and programs; researchers of socio-economic processes associated with the development of the information society and the economy, and the increasing distribution of digital data processing technologies. The analysis of the digitalization process in the country and the world allowed us to identify problems that require close attention and finding solutions for the implementation of project activities for the formation of a modern digital educational environment in the Russian Federation. Novelty/Originality of this study: The novelty and originality of the study lies in the fact that for the first time it offers a comprehensive approach to assessing the specifics and factors of the digitalization process in the educational space of the country, developing mechanisms to reduce threats to information security by developing a system for identifying users, technical controls, and improving the legislative framework.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".